Strategi Peningkatan Kualitas Permukiman berdasarkan Livable Settlement RW 10 Rancaekek Kencana
Bibliographic record
Abstract
Abstract. Urbanization in Indonesia continues to increase, with an estimated 60% of the population living in cities by 2025. This phenomenon demands the concept of livable settlement to create livable, comfortable and sustainable settlements. This research was conducted in RW 10 Kelurahan Rancaekek Kencana, Bandung Regency, with the aim of evaluating the quality of settlements based on livable settlement criteria and designing strategies to improve them. The research method used qualitative and quantitative approaches through field observations, interviews, literature studies, institutional surveys, as well as descriptive and SWOT analysis. The results showed a number of problems, such as limited public transportation, lack of green open space (RTH), poor waste management, unmaintained drainage system, and road infrastructure that does not meet the standards. On the other hand, potentials such as the availability of education, health, and worship facilities can be optimized to support the quality of life of the community. The proposed strategies include vertical green space development, integrated waste management, improved transportation and infrastructure, and environmental education programs for the community. This strategy is expected to improve the quality of life, comfort, and sustainability of the settlement environment in RW 10. Active collaboration between the community and the government is key in realizing a settlement that is in accordance with the concept of livable settlement. Abstrak. Urbanisasi di Indonesia terus meningkat, dengan estimasi 60% populasi akan tinggal di perkotaan pada tahun 2025. Fenomena ini menuntut adanya konsep livable settlement untuk menciptakan permukiman yang layak huni, nyaman, dan berkelanjutan. Penelitian ini dilakukan di RW 10 Kelurahan Rancaekek Kencana, Kabupaten Bandung, dengan tujuan mengevaluasi kualitas permukiman berdasarkan kriteria livable settlement dan merancang strategi peningkatannya. Metode penelitian menggunakan pendekatan kualitatif dan kuantitatif melalui observasi lapangan, wawancara, studi literatur, survei instansional, serta analisis deskriptif dan SWOT. Hasil penelitian menunjukkan sejumlah permasalahan, seperti keterbatasan transportasi umum, minimnya ruang terbuka hijau (RTH), buruknya pengelolaan sampah, sistem drainase yang tidak terpelihara, serta infrastruktur jalan yang belum memenuhi standar. Di sisi lain, potensi seperti tersedianya fasilitas pendidikan, kesehatan, dan peribadatan dapat dioptimalkan untuk mendukung kualitas hidup masyarakat. Strategi yang diusulkan meliputi pembangunan RTH vertikal, pengelolaan sampah terintegrasi, peningkatan transportasi dan infrastruktur, serta program edukasi lingkungan bagi masyarakat. Strategi ini diharapkan dapat meningkatkan kualitas hidup, kenyamanan, dan keberlanjutan lingkungan permukiman di RW 10. Kolaborasi aktif antara masyarakat dan pemerintah menjadi kunci dalam mewujudkan permukiman yang sesuai dengan konsep livable settlement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".